Welcome!

The Austin Chapter of SIAM is a society for all those interested in
mathematics and its applications. We sponsor guest speakers, career
discussions on industry and academia, student-faculty social events, and
visits to annual SIAM meetings. We welcome new members from all majors
and all University of Texas at Austin members, whether undergraduate,
graduate, faculty, or other.

Spring 2016 SIAM Coffee Breaks

We will once again have Biweekly Coffee Breaks this semester, starting February 10 at 11:30 A.M. at POB 6.102. We hope you will join us!

"[The group] is open to all students interested in mathematics,
and especially caters to the UT-Austin pure and applied
mathematics communities. Our goal is to enhance the undergraduate
math experience by exposing students to beautiful mathematics,
interesting research, and helpful information every week."

Useful Packages

This package is the principal package in the AMS-LaTeX
distribution. It adapts for use in LaTeX most of the mathematical
features found in AMS-TeX; it is a near-indispensable adjunct
to serious mathematical typesetting in LaTeX.

The package provides extensive facilities, both for constructing
headers and footers, and for controlling their use (for example,
at times when LaTeX would automatically change the heading style
in use).

An extensive collection of PostScript macros that is compatible
with most TeX macro formats, including Plain TeX, LaTeX, AMS-TeX,
and AMS-LaTeX. Included are macros for colour, graphics, pie
charts, rotation, trees and overlays.

Programming help

"TACC offers various training classes in high performance computing
(HPC), scientific visualization (SciVis), distributed and grid
computing (DGC), and computational cluster management. TACC
training classes teach the programming principles and techniques
in HPC and SciVis as well as how to use TACC's high-end systems
most effectively."

"Many scientists and engineers spend much of their lives
programming, but only a handful have ever been taught how to do
this well. ... This course is an intensive introduction to basic
software development practices for scientists and engineers that
can reduce the time they spend programming by 20-25%."

"This tutorial covers the very basics of parallel computing,
and is intended for someone who is just becoming acquainted with
the subject. It begins with a brief overview, including concepts
and terminology associated with parallel computing. The topics
of parallel memory architectures and programming models are then
explored. These topics are followed by a discussion on a number
of issues related to designing parallel programs. The tutorial
concludes with several examples of how to parallelize simple
serial programs."

"TACC scientists are teaching ... undergraduate and graduate level
courses at The University of Texas at Austin, in the Division of
Statistics and Scientific Computation. The courses are designed
to enable students to apply scientific computing in research
and development for both academic and industry careers."

Presentation tips

Have an outline of the talk on the title page or the first slide so the audience knows where you're going.

Have a short topic header at the top of each slide.

Don't use complete sentences on the slide.

Don't put too much on a slide.

If you have animations, make sure the talk can proceed even if they don't work.

Make sure the font size is large enough to read. Make sure it has enough contrast to read it - light text on dark background or dark text on light background. Don't use strange fonts.

Use graphics and pictures in your slides.

For a graph, have a title and labels for the axes with units.

Don't try to cover too much - a one term course cannot be covered in an hour.

Don't introduce too much jargon.

Don't do a long derivation.

If you do a derivation or a proof, make sure you first write what you are trying to derive or prove. That way, when people get lost, they can look at the top of the board and see where they are trying to go to and where from.

When you have an important equation, try to have a physical or conceptual explanation of it too.

Don't introduce too many new variables.

Practice the talk by yourself and in front of others. Have them give you suggestions for improvement.

During the presentation, look at the audience and make eye contact with a number of people.

Speak loud enough for people to hear you.

Avoid saying fluff words, such as "uh" and "basically."

If you stumble verbally, do not apologize but continue.

Do not rush the presentation.

Look at the computer screen or a print-out of your slides, not the screen behind you.

Do not read your slides or have your presentation memorized word-for-word, but speak about your work from the bullets on the slide or from notes.

Smile.

Stop talking periodically and ask questions to make sure everyone is keeping up with you. In your practice, time the presentation to allow for a few minutes of questions at the end. At the last, ask the question "Are there any questions?"

You should spend at least 75% of your time looking at your audience and at most 25% of your time looking at the blackboard. First-time speakers often spend 100% of their time looking at the blackboard

Plan a closing line. Even if you give a great talk, ending it with "Um, I guess that's all I've got" or "I think that's the last slide" will do nothing for your cause. Say something like "That concludes my presentation--thank you for your attention" or "I'll be happy to take questions now--thanks for coming " or simply "Thank you."

Rules of procedure

This Rules of Procedure (hereinafter called "Rules") apply to the SIAM
student chapter called “UT Austin Chapter of SIAM".

The Chapter to which these Rules apply is formed by the Society for
Industrial and Applied Mathematics and shall operate within the Bylaws of
the parent organization. The SIAM bylaws specify how Chapters are formed;
see the SIAM bylaws for details. The Chapter shall not affiliate with any
other organization without first obtaining the written approval of SIAM.
Provisions for SIAM Student (University) Chapters are contained in the
SIAM Bylaws and are included in these Rules. No provisions of these
rules shall be construed so as to contradict the Bylaws of SIAM.

Article I: Purpose

The objectives of SIAM, as established in the Certificate of
Incorporation, are:

To further the application of mathematics to industry and science.

To promote basic research in mathematics leading to new methods
and techniques useful to industry and science.

To provide media for the exchange of information and ideas between
mathematicians and other technical and scientific personnel.

The objectives of the UT Austin Student Chapter of SIAM are:

To promote interactions between members of the applied mathematics
community at UT Austin, across departments, institutes, and
professional ranks;

To provide a forum for the discussion of applied and computational
mathematics research and pedagogy;

To help members prepare for future careers in applied and
computational mathematics;

To promote publications, conferences, prizes, and other
opportunities offered by SIAM;

Annual elections for Chapter officers, beginning in November 2005,
for calendar-year terms of service;

Article III: Institution Served

Members shall be recruited from The University of Texas at Austin.

Article IV: Membership

Section 1

Any person engaged or interested in mathematics or computing
and their applications shall be eligible for membership in
this Chapter. Chapter membership may be interdisciplinary,
with members from multiple departments.

Section 2

There are no dues.

Section 3

Chapter members shall have the privileges of SIAM membership
only if they are regular or student members of SIAM.

Section 4

All members of the chapter who are students enrolled in
the sponsoring institution(s) are eligible for free student
memberships in SIAM. The chapter is responsible for providing
a list of its student members to SIAM so that complimentary
student membership in SIAM can be processed.

Section 5

Termination of student membership will take place upon
graduation or withdrawal from the university.

Article V: Sponsorship

Section 1

The Sponsor is UT Austin.

Section 2

The Sponsor of the Chapter shall appoint two Faculty Advisors
for the Chapter. One of these must be affiliated with the UT
Austin Mathematics Department. One of these must be affiliated
with the Institute for Computational Engineering and Sciences
(ICES). In the event either Advisor relinquishes his/her position,
the Sponsor shall appoint a new Advisor. The responsibilities,
rights and duties of the Faculty Advisor shall be those normally
assigned to the Faculty Advisor of student organizations of the
Sponsor, but in addition, the Faculty Advisor is expected to
take leading role in the development of the Chapter activities
consistent with the objectives of SIAM.

Article VI: Officers

Section 1

The Chapter shall have a President, a Vice-President, and a
Secretary-Treasurer. Officers shall be Student Members in good
standing with SIAM, and shall be chosen from Student Members of
the Chapter.

Section 2

The President shall preside at the meetings of the Chapter (and
the Chapter Executive Committee, see Article VII below). The
president must be a graduate student at UT Austin. In the
absence of the President, the Vice-President shall assume the
duties of the President. In the absence of the latter, the
Secretary-Treasurer shall assume said duties.

Section 3

The Secretary-Treasurer shall keep a record of the affairs
of the Chapter, handle correspondence, and submit an annual
report of Chapter activities to the Secretary of SIAM, which
report shall be suitable for publication in SIAM News
or its equivalent. The Secretary-Treasurer shall receive and
take custody of Chapter funds, and shall submit an annual
Treasurer's Report and other financial reports, as requested,
to the Treasurer of SIAM. The annual Treasurer's Report shall
be prepared as of the end of the academic year and shall be
transmitted to the Treasurer of SIAM by no later than 30 days
following the end of the academic year.

Section 5

Elections will be held yearly near the end of the Fall
semester. Elections may be held earlier in the Fall of
2005 in order to fill the positions of Vice-President and
Secretary-Treasurer.

Article VII: Executive Committee

Section 1

The Executive Committee will consist of the President, Vice
President, and Secretary-Treasurer. The President is the
Committee chair. The Executive Committee is responsible for
planning meetings, organizing elections, and maintaining a
website. It should have at least quarterly meetings to discuss
plans for the chapter.

Section 2

In the event of a vacancy, members shall be notified (by email)
and elections held two weeks later.

Article VIII: Other Committees

Section 1

Nominations for officers should be sent to the member of the
Executive Committee specified in the announcement of the election.

Article X: Meetings

Section 1

There shall be at least three chapter meetings per year.
Meetings will be scheduled and planned by the Executive Committee.

Section 2

The Chapter shall conduct a business meeting once per year during
the month of September. Other business meetings may be called
by the President or the Treasurer on two weeks notice.

Article XI: Chapter Funds

Section 1

The Chapter shall deposit all unused funds to which it has legal
title in excess of $200 in an insured savings account, unless
current operating commitments are in excess of that amount or
unless the Chapter Treasurer obtains a written authorization
from the SIAM Treasurer.

Section 2

The Treasurer shall maintain books of account that show
income and expense items for all activities and balances for all
accounts of the Chapter.

Section 3

The Chapter may request a grant or loan from the Treasurer of SIAM
under the provision of Article XII, Chapter 8 of the Bylaws of
SIAM. Such requests shall be made by submission of “Request for
Funding” form to SIAM and include a current financial statement
for the Chapter and a proposed budget for the requested funds.

Section 4

Other than seeking funds from the sponsoring institutions of
the chapter, no officers or member of the Chapter may apply
for a grant to support the Chapter activities or enter into
any contract to support such activities or provide services,
without approval of the President and the Treasurer of SIAM or
the Executive Director acting on behalf of the Treasurer.

Article XII: Amendments

Section 1

These Rules may be altered or amended with the approval of the
SIAM Board of Trustees. Submission to the board of proposal
alterations or amendments shall be made only after approval by
majority vote of members of the Chapter present (or represented
by proxy) at a scheduled meeting. Before the scheduled meeting,
a notice of the upcoming vote shall be sent (by email) to all
members at least 1 week in advance.

Article XIII: Termination of the Chapter

Section 1

A Chapter may terminate itself by the unanimous vote of the
members of the Chapter present (or represented by proxy)
at a scheduled meeting, provided that notice of the proposed
termination and the meeting at which it is to be considered has
been given to all Chapter members at least 30 days in advance.

Section 2

A Chapter may be terminated by the board if there has been no
Chapter activity for one year.

Section 3

In the event a Chapter terminates, the funds to which it has
legal title shall revert to the account of SIAM.

SIAM prizes for students

"The SIAM Student Paper Prizes are awarded every year to the
student author(s) of the most outstanding paper(s) submitted to
the SIAM Student Paper Competition. This award is based solely
on the merit and content of the student's contribution to the
submitted paper. The purpose of the Student Paper Prizes is
to recognize outstanding scholarship by students in applied
mathematics or computing."

"The SIAM Award in the Mathematical Contest in Modeling (MCM),
established in 1988, is awarded to two of the teams judged
'Outstanding' in the Mathematical Contest in Modeling (MCM),
administered annually by the Consortium for Mathematics and Its
Applications (COMAP). One winning team is chosen for each of
the two problems (continuous and discrete) posed in the MCM."

"The Morgan Prize was established in 1995 and is awarded annually
to an undergraduate student (or students having submitted joint
work) for outstanding research in mathematics. It is entirely
endowed by a gift from Mrs. Frank (Brennie) Morgan. Any student
who is an undergraduate in a college or university in Canada,
Mexico, the United States or its possessions is eligible to
be considered for the prize. The award is made jointly by the
American Mathematical Society, the Mathematical Association of
America, and the Society for Industrial and Applied Mathematics."

"SIAM offers travel support for students through SIAM Student
Travel Awards. The awards are made from the SIAM Student Travel
Fund, created in 1991 and maintained through book royalties
donated by generous SIAM authors and by donations from SIAM
members. The awards for selected conferences are also supported by
donations from industry. Any full-time student in good standing
is eligible to receive an award plus gratis meeting registration."

"The mission of SIAM's book program is to make relevant research
results accessible to industry and science and to promote the
interaction between mathematics and other disciplines such as
engineering, science, and computing."

"SIAM conferences focus on timely topics in applied and
computational mathematics and applications and provide a place
for members to exchange ideas and to expand their network of
colleagues in both academia and industry."

SIAM student travel awards

Any full-time student in good standing is eligible to receive an award
plus gratis meeting registration. Top priority will be given to students
presenting papers at the meeting, with second priority to students who are
co-authors of papers to be presented at the meetings. Only students
traveling more than 100 miles to the meetings are eligible for the
awards.

An application for a travel award must include:

A letter from the student describing his/her academic standing and
interests, his/her expected graduation date and degree, advisor's name,
and, if available, a URL for a working Web page.

A one-page vita that includes the student's research interests,
projects, and papers published.

A detailed letter from the student's faculty advisor indicating why
the student is deserving of receiving a travel award and any special
circumstances.

If applicable, the title(s) of the paper(s) to be presented
(co-authored) by the student at the meeting.

In most cases, the deadline for complete applications is approximately
seven months before the first day of the conference for which support
is requested, and awardees will be notified by e-mail five months before
the first day of the meeting.

UT graduate student professional development awards

"Professional
Development Awards provide support for students to attend major
professional meetings at which they present an original paper based
on their research. The Graduate School allocates travel funds to each
department or program. The graduate adviser and graduate coordinator can
nominate students for these awards which are approved and administered
by the Graduate School."

Keynote speaker: Dr. Raegan Higgins

TAMMS was proud to have Dr. Raegan Higgins give the keynote at our
conference. She presented on Friday, March 27th in CPE 2.212
at 4:45 PM.

"An Introduction to the Time Scale Calculus"

A time scale T is just a closed nonempty subset of the real numbers. Time
scales include the real numbers, the integers, and the Cantor set. Given a
smooth function p(t) defined on a time scale and a point s in the time scale we
will define a generalized exponential function ep(t,s) which
generalizes the exponential function ept studied in calculus.

Brief Biography

Raegan Higgins received a B.S. degree in mathematics from Xavier
University of Louisiana in 2002 , and the degrees of M.S. (2004) and
Ph.D. (2008) from the University of Nebraska-Lincoln. Her dissertation
work was in the area of oscillation criteria for dynamic equations on
time scales.

Dr. Higgins' current research is in time scales; her interests focus on
oscillation criteria for certain linear and nonlinear second order dynamic
equations. She is also interested in issues that affect pre-service teachers
ability to teach mathematics.

Texas Applied Mathematics Meeting for Students

The Austin Chapter of SIAM was proud to host the 2009 Texas Applied Mathematics
Meeting for Students (TAMMS) on March 27–28th. Attendees had an
opportunity both to present their own research and to meet fellow SIAM student
members from other Texas institutions.

Parking

We recommend that visitors to our campus park at either the Speedway
Garage (SWG) or the 27th Street Garage (TSG). From the Speedway garage,
it will take you seven minutes to walk to either CPE on Friday or RLM
on Saturday. From the 27th street garage, it will take you ten
minutes to walk to these two buildings.

Meeting Schedule

Friday, March 27th 2009 in CPE 2.212

2:00–2:30 PM

Arrival & registration

2:30–2:45 PM

Welcoming remarks

2:45–3:15 PM

James Martin

Computational and Applied Mathematics

UT Austin

A Stochastic Newton's Method for Bayesian Inverse Problems

We present a new MCMC method for sampling high-dimensional,
expensive-to-evaluate probability density functions. We improve
upon Langevin sampling by using local Hessian information to
guide sampling, drastically improving acceptance probabilities
and MCMC convergence rates. The resulting method resembles a
stochastic variant of Newton's method. We demonstrate by
solving a statistical inverse problem governed by 1D seismic
wave propagation with up to 65 parameter dimensions, for which
the new method is two orders of magnitude faster than
conventional MCMC.

3:15–3:45 PM

Yulia Hristova

Mathematics

Texas A&M University

Time reversal in thermoacoustic tomography - an error estimate

In thermoacoustic tomography an object is irradiated by
a short electromagnetic pulse and the absorbed energy
causes a thermoelastic expansion. This expansion leads
to a pressure wave propagating through the object. The
goal of thermoacoustic tomography is the recovery of the
initial pressure inside the object from measurements
of the pressure wave made on a surface surrounding
the object. The time reversal method can be used for
approximating the initial pressure when the sound speed
inside the object is variable (non-trapping as well
as trapping).

In this talk I will present error estimates for the time
reversal method in the cases of variable, non-trapping
sound speeds.

Calcium plays an important role in neuroscience. Not only is it
involved in the pathways that govern learning events in
neurons, but it is increasingly being used as the primary means
of accessing information about the neuron's state.
Unfortunately, for most physiologists, calcium information is
an incomplete picture of the neuron.

We developed an algorithm to convert fluorescent calcium data
into voltage and conductance information. We simulate our
algorithm on synthetic data to illustrate its usefulness.

4:15–4:45 PM

Coffee Break

4:45–5:30 PM

Dr. Raegan Higgins

Mathematics and Statistics

Texas Tech University

An Introduction to the Time Scale Calculus

A time scale T is just a closed nonempty subset of the real
numbers. Time scales include the real numbers, the integers,
and the Cantor set. Given a smooth function p(t) defined on a
time scale and a point s in the time scale we will define a
generalized exponential function ep(t,s) which
generalizes the exponential function ept studied in
calculus.

Ultrasound Modulated Optical Tomography attempts to improve the
severe ill-posedness of the reconstruction problem arising in
classical Optical Tomography by combining the advantages of
Optical Tomography with those of ultrasound imaging. In this
talk, a model is introduced that describes the effect of
ultrasound modulation on the light intensity by two coupled
diffusion equations, one for the original, unaffected photon
intensity and one for a second, virtual intensity field
modulated at ultrasound frequency.

In contrast to previous statistics-based approaches, this model
allows reconstruction of the absorption coefficient by using
efficient, PDE-based solutions for the forward problem. A
simple reconstruction algorithm is introduced to demonstrate
the feasibility of this reconstruction for 2D problems and
well-focused ultrasound signals. For the more realistic case of
non-focused ultrasound signals, reconstruction techniques based
on inversion of certain integral transforms are suggested. For
both of these cases, numerical reconstruction results for
artificial absorption phantoms are presented.

Saturday, March 28th 2009 in RLM 4.102

8:00–8:30 AM

Sean Hardesty

Computational and Applied Mathematics

Rice University

Optimization of Shell Structure Acoustics

Modeling of elastic shell structures coupled with
acoustics in a way that is suitable for optimization poses
a multitude of challenges. For the exterior problem, it
is convenient to use shell elements in conjunction with
boundary elements so that shape updates can be performed
without modifying the mesh. In order to do so, the shell
code must be free of the so-called locking phenomenon, and
the boundary element code must be robust and reasonably
fast. With the aim of making the implementation of the
coupling and adjoint equations as simple as possible,
we describe a scheme satisfying these criteria, and
present some numerical results.

Simulating active neurons with realistic morphologies and
synaptic inputs requires the solution of large systems of
nonlinear ordinary differential equations. Using model
reduction techniques of proper orthogonal decomposition
and an empirical interpolation method, we recover the
complete neuronal voltage dynamics using a system of
dimension nearly two orders of magnitude smaller than
the original and that simulates one order of magnitude
faster, without sacrificing the spatially-distributed
input structure.

9:00–9:30 AM

Yan Li

Mathematics

Texas A&M University

Local-Global Upscaling of Flow and Transport in heterogeneous
porous media

Flow and transport in subsurface formations are affected
by geological variability over multiple length scales. We
develop a local-global two-phase upscaling approach to
generate upscaled transport functions. The upscaling
of multiphase flow parameters is challenging due to
their strong dependency on global flow effects. The
local-global two-phase upscaling directly incorporates
global coarse-scale two-phase solutions into local
two-phase upscaling calculations. It effectively captures
the impact of global flow, while avoiding global
two-phase fine-scale simulations. The local boundary
conditions are updated with time-dependent coarse-scale
solutions. It therefore captures the global flow effects
both spatially and temporally. The method is applied
to permeability distributions with various correlation
lengths. Numerical results show that it consistently
improves existing two-phase upscaling methods (e.g.,
upscaling with effective flux boundary conditions),
and provides accurate coarse-scale solutions for both
flow and transport.

9:30–10:00 AM

Ryan Nong

Computational and Applied Mathematics

Rice University

Numerical Solutions of Matrix Equations Arising in Model Order
Reduction for Linear-Time-Invariant Systems in the Large-Scale
Setting

Balanced truncation and positive real balancing techniques in
dimension reduction for linear-time-invariant dynamical systems
require the solution of multiple large-scale matrix equations.
Current iterative solvers include the approximate power method
(APM) and the alternating direction implicit (ADI) method. The
former is parameter free and tends to be efficient in practice
but there is little theoretical understanding of its
convergence properties. The latter has a well understood
convergence theory but relies heavily upon heuristic parameter
selection for rapid convergence. In this talk, I will first
introduce a novel algorithm that is based on a synthesis of the
two aforementioned techniques. This parameter free ADI-like
(PFADI) technique uses an APM iteration as a means to bypass
the trouble in parameter selection of the ADI method but still
preserves its convergence properties. I will then present new
results in optimizing the performance of the PFADI method.

In this talk I will discuss the main difficulties that arise
when employing the finite element method to approximately solve
PDEs posed on infinite domains. I will then present a simple
way of overcoming them for the cases of exterior Laplace and
Helmholtz problems. Additionally this talk will serve as an
introduction to the Perfectly Matched Layer technique - the
leading artificial boundary condition for acoustic and
electromagnetic scattering problems.

11:00–11:30 AM

Robert Rosenbaum

Mathematics

University of Houston

Correlation Propagation in Networks of Integrate-and-Fire Neurons

Experimental results show that correlations between the spiking
activity of neurons are used to encode information about some
stimuli. However, experimental and theoretical results show
that excess correlation can accumulate in feedforward networks
and lead to pathological spiking behaviors. I will discuss
some work on correlation transfer properties of analytically
tractable neuron models and implications on the activity of
feedforward networks.

11:30–12:00 AM

Linh Nguyen

Mathematics

Texas A&M University

On inversion formula in Thermoacoustic Tomography

We present a family of inversion formulas in Thermoacoustic
Tomography that contains as special cases most of previously
known closed form reconstructions for acoustically homogeneous
media.

We consider the problem of estimating and propagating the
uncertainty in the initial condition field of a
convection-diffusion problem describing the transport of
atmospheric contaminants. Estimation of the uncertainty is
treated within a Bayesian framework. Standard Markov chain
Monte Carlo approaches are intractable for such
high-dimensional problems. Even when the data and prior
uncertainty are Gaussian, and as a result the posterior
estimate is Gaussian with covariance given by the inverse of
the Hessian matrix of the regularized least squares objective,
the computation of the exact covariance matrix is intractable
due to the large size and extreme cost of forming the inverse
of the Hessian. In the case of linear ill-posed inverse
problems, we show that fast algorithms can be constructed that
provide accurate low rank Hessian approximations of the least
squares data misfit, and as a result permit estimation and
propagation of the uncertainty for large-scale problems at a
small multiple of the cost of solving the forward problem.
Large-scale examples demonstrate the main ideas.

CSE Success Stories: Storm Surge UNDER CONSTRUCTION

Fig. 1 - Results of a simulated severe hurricane directly impacting the Houston region. Maximum water surface elevation (in meters) over duration of simulation.Fig. 2 - Results of simulated severe hurricane with “Centennial Gate" in place. Note resulting protection of greater Houston area above shipping channel (in blue) in comparison to top figure without gate. Maximum water surface elevation (in meters) over duration of simulation.Fig. 3 - Results of simulated severe hurricane with “Coastal Spline" in place. Note resulting protection of Galveston Bay (light blue) in comparison to top figure without levee. Maximum water surface elevation (in meters) over duration of simulation.
Your browser does not support the video tag.

Time history of water elevation for Mega Hurricane Ike, storm track 7.

At the forefront of scientific research, Computational Science and Engineering plays a critical role in analyzing and predicting the behavior of complex physical systems. A significant application is the modeling of hurricane storm surge, a natural phenomena which wreaks major damage on coastal communities every year. Long known for its damaging effects, storm surge is difficult to predict and has been responsible for the loss of thousands of lives and billions of dollars in damages along the Texas and Louisiana Gulf coasts in particular.

The ability to accurately model and subsequently communicate results effectively is crucial to decision makers both during the emergency phase of an impacting storm, and off season during which structural and non-structural mitigation strategies are planned. Sea walls and levees have been built in an attempt to protect lives and communities from the onslaught of this powerful force, and additional solutions are consistently proposed. The National Oceanic and Atmospheric Administration, U.S. Army Corp of Engineers, as well as academic researchers, all use CS&E modeling to help make informed decisions. Clearly the impact of hurricane storm surge modeling is large scale, directly influencing current decision making and the planning of future strategies to reduce the impact of these natural disasters.

Major initiatives are currently underway by the Computational Hydraulics Group (CHG) at The University of Texas at Austin and collaborators to research and design the next generation of highly accurate computational storm surge modeling and analysis. We highlight here two such areas of current research underway.

In collaboration with Rice University’s Severe Storm Prediction Education and Evacuation from Disasters (SSPEED) Center, researchers are developing a comprehensive strategy to prepare and protect the Houston-Galveston region from hurricanes. Computational modeling is a critical tool to predict the severity of storms and to evaluate the effectiveness of proposed surge reduction ideas prior to implementation. Where and what is chosen to construct may have far reaching effects, either increasing or decreasing potential damage. Planners and policy makes can better understand which mitigation developments function well as barriers to the sea and limit development in these areas.

Results of CHG work yield a Houston Galveston Area Protection System (H-GAPS), which includes the “Coastal Spline”— a proposed multibillion-dollar seawall that would enhance the existing wall and expand it to run the length of Galveston Island and Bolivar Peninsula. Alternatively, a “Centennial Gate” would close off the upper portion of the shipping channel to protect the greater Houston region (Figure 2). To evaluate the effectiveness of these structures, computational modelers simulate a severe storm directly impacting the most vulnerable region of greater Houston and Galveston (Figure 1 and 2).

To efficiently generate data regarding potential outcomes, the use of high performance computers is essential due to the complexity of the hydrological model. The National Science Foundation recently funded CHG’s STORM project, an initiative designed to enhance the current performance of computational storm surge model functionality.

Driven by increased performance, computational hardware is becoming more powerful and diverse in terms of components. For a predictive model to achieve optimal performance across systems, scientific computing must keep up with state-of-the-art invention. The High Performance ParallelX (HPX) code currently under development in the STORM project is a completely new foundation that is designed to be flexible and easily integrable with other architectures. By utilizing HPX, the software enables computations to run more efficiently on modern supercomputing systems. Moreover, it is well equipped to handle the inevitable future of hardware development.

Acknowledgements:

CSE Success Stories: Storm Surge

Fig. 1 - Results of a simulated severe hurricane directly impacting the Houston region. Maximum water surface elevation (in meters) over duration of simulation.Fig. 2 - Results of simulated severe hurricane with “Centennial Gate" in place. Note resulting protection of greater Houston area above shipping channel (in blue) in comparison to top figure without gate. Maximum water surface elevation (in meters) over duration of simulation.Fig. 3 - Results of simulated severe hurricane with “Coastal Spline" in place. Note resulting protection of Galveston Bay (light blue) in comparison to top figure without levee. Maximum water surface elevation (in meters) over duration of simulation.
Your browser does not support the video tag.

Time history of water elevation for Mega Hurricane Ike, storm track 7.

At the forefront of scientific research, Computational Science and Engineering plays a critical role in analyzing and predicting the behavior of complex physical systems. A significant application is the modeling of hurricane storm surge, a natural phenomena which wreaks major damage on coastal communities every year. Long known for its damaging effects, storm surge is difficult to predict and has been responsible for the loss of thousands of lives and billions of dollars in damages along the Texas and Louisiana Gulf coasts in particular.

The ability to accurately model and subsequently communicate results effectively is crucial to decision makers both during the emergency phase of an impacting storm, and off season during which structural and non-structural mitigation strategies are planned. Sea walls and levees have been built in an attempt to protect lives and communities from the onslaught of this powerful force, and additional solutions are consistently proposed. The National Oceanic and Atmospheric Administration, U.S. Army Corp of Engineers, as well as academic researchers, all use CS&E modeling to help make informed decisions. Clearly the impact of hurricane storm surge modeling is large scale, directly influencing current decision making and the planning of future strategies to reduce the impact of these natural disasters.

Major initiatives are currently underway by the Computational Hydraulics Group (CHG) at The University of Texas at Austin and collaborators to research and design the next generation of highly accurate computational storm surge modeling and analysis. We highlight here two such areas of current research underway.

In collaboration with Rice University’s Severe Storm Prediction Education and Evacuation from Disasters (SSPEED) Center, researchers are developing a comprehensive strategy to prepare and protect the Houston-Galveston region from hurricanes. Computational modeling is a critical tool to predict the severity of storms and to evaluate the effectiveness of proposed surge reduction ideas prior to implementation. Where and what is chosen to construct may have far reaching effects, either increasing or decreasing potential damage. Planners and policy makes can better understand which mitigation developments function well as barriers to the sea and limit development in these areas.

Results of CHG work yield a Houston Galveston Area Protection System (H-GAPS), which includes the “Coastal Spline”— a proposed multibillion-dollar seawall that would enhance the existing wall and expand it to run the length of Galveston Island and Bolivar Peninsula. Alternatively, a “Centennial Gate” would close off the upper portion of the shipping channel to protect the greater Houston region (Figure 2). To evaluate the effectiveness of these structures, computational modelers simulate a severe storm directly impacting the most vulnerable region of greater Houston and Galveston (Figure 1 and 2).

To efficiently generate data regarding potential outcomes, the use of high performance computers is essential due to the complexity of the hydrological model. The National Science Foundation recently funded CHG’s STORM project, an initiative designed to enhance the current performance of computational storm surge model functionality.

Driven by increased performance, computational hardware is becoming more powerful and diverse in terms of components. For a predictive model to achieve optimal performance across systems, scientific computing must keep up with state-of-the-art invention. The High Performance ParallelX (HPX) code currently under development in the STORM project is a completely new foundation that is designed to be flexible and easily integrable with other architectures. By utilizing HPX, the software enables computations to run more efficiently on modern supercomputing systems. Moreover, it is well equipped to handle the inevitable future of hardware development.

At the forefront of scientific research, Computational Science and Engineering plays a critical role in analyzing and predicting the behavior of complex physical systems. A significant application is the modeling of hurricane storm surge, a natural phenomena which wreaks major damage on coastal communities every year. Long known for its damaging effects, storm surge is difficult to predict and has been responsible for the loss of thousands of lives and billions of dollars in damages along the Texas and Louisiana Gulf coasts in particular.

The ability to accurately model and subsequently communicate results effectively is crucial to decision makers both during the emergency phase of an impacting storm, and off season during which structural and non-structural mitigation strategies are planned. Sea walls and levees have been built in an attempt to protect lives and communities from the onslaught of this powerful force, and additional solutions are consistently proposed. The National Oceanic and Atmospheric Administration, U.S. Army Corp of Engineers, as well as academic researchers, all use CS&E modeling to help make informed decisions. Clearly the impact of hurricane storm surge modeling is large scale, directly influencing current decision making and the planning of future strategies to reduce the impact of these natural disasters.

Major initiatives are currently underway by the Computational Hydraulics Group (CHG) at The University of Texas at Austin and collaborators to research and design the next generation of highly accurate computational storm surge modeling and analysis. We highlight here two such areas of current research underway.

In collaboration with Rice University’s Severe Storm Prediction Education and Evacuation from Disasters (SSPEED) Center, researchers are developing a comprehensive strategy to prepare and protect the Houston-Galveston region from hurricanes. Computational modeling is a critical tool to predict the severity of storms and to evaluate the effectiveness of proposed surge reduction ideas prior to implementation. Where and what is chosen to construct may have far reaching effects, either increasing or decreasing potential damage. Planners and policy makers can better understand which mitigation designs function well as barriers to the sea and subsequently limit development in these areas.

Results of CHG research yield a Houston Galveston Area Protection System (H-GAPS), which includes the “Coastal Spline”— a proposed multibillion-dollar seawall that would enhance the existing wall and expand it to run the length of Galveston Island and Bolivar Peninsula. Alternatively, a “Centennial Gate” would close off the upper portion of the shipping channel to protect the greater Houston region (Figure 2). To evaluate the effectiveness of these structures, computational modelers simulate a severe storm directly impacting the most vulnerable region of greater Houston and Galveston (Figure 1 and 2).

To efficiently generate data regarding potential outcomes, the use of high performance computers is essential due to the complexity of the hydrological model. The National Science Foundation recently funded CHG’s STORM project, an initiative designed to enhance the current performance of computational storm surge model functionality.

Driven by increased performance, computational hardware is becoming more powerful and diverse in terms of components. For a predictive model to achieve optimal performance across systems, scientific computing must keep up with state-of-the-art invention. The High Performance ParallelX (HPX) code currently under development in the STORM project is a completely new foundation that is designed to be flexible and easily integrable with other architectures. By utilizing HPX, the software enables scientific computations to run more efficiently on modern supercomputing systems. Moreover, it is well equipped to handle the inevitable future of hardware development.

Organization resources

Location

On Friday, March 27th the conference was in the Chemical and Petroleum
Engineering Building (CPE) room 2.212. On Saturday, March 28th the conference
was in in Robert Lee Moore Hall (RLM) room 4.102. Both buildings are at the
corner of Speedway & E Dean Keeton St in the Engineering Area of the
University of Texas at Austin campus.